Data Engineer (GIS preferred)

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Optimum Solutions

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Job Summary


Job Type
-

Seniority

Years of Experience
Information not provided

Tech Stacks
Python GeoPandas Flow PostGIS ArcGIS Server Analytics Data Extraction

Job Description

Responsibilities


  • Design, develop and deploy data tables, views and marts in data warehouses, operational data store, data lake and data virtualization.
  • Perform data extraction, cleaning, transformation, and flow.
  • Design, build, launch and maintain efficient and reliable large-scale batch and real-time data pipelines with data processing frameworks.
  • Integrate and collate data silos in a manner which is both scalable and compliant.
  • Collaborate with Product Manager, Data Architect, Business Analysts, Frontend Developers, Designers and Data Analyst to build scalable data-driven products.
  • Be responsible for developing backend APIs & working on databases to support the applications.
  • Work in an Agile Environment that practices Continuous Integration and Delivery.
  • Work closely with fellow developers through pair programming and code review process.


GIS / Spatial


  • Familiar with GIS platforms: ArcGIS Server, PostGIS.
  • Able to use spatial Python libraries: GeoPandas, Shapely.
  • Build scalable geospatial data pipelines for ingestion, transformation, storage, and quality checks from multiple government sources.
  • Implements data cataloging, metadata, lineage, and security; optimizes storage and performance for GIS analytics (e.g., PostGIS, data lakes).
  • Provides reliable data services and contracts to support downstream GIS analytics and front-end visualizations, collaborating closely with GIS and frontend teams.
  • Data management: applies validation, cleansing, reprojection, metadata, and data lineage of geospatial data.
  • Designs enterprise geospatial data models, schemas, pipelines, and services; builds or configures web map services and front-end visualization components.
  • Ensures data quality, standards compliance (ISO 19115/19139, OGC), governance, and operational reliability of GIS data assets.

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